Systems and methods for automated remote network performance monitoring

ABSTRACT

In some implementations, a device may determine one or more parameters for filtering network traffic of a network that includes a plurality of virtual packet brokers provided for a plurality of cloud random access networks and a plurality of traffic aggregation points. The device may provide the one or more parameters to the plurality of virtual packet brokers, to cause the plurality of virtual packet brokers to filter the network traffic to obtain network visibility traffic. The device may receive, from one or more probes of a session aggregation point of the network, one or more metrics calculated based on the network visibility traffic by the plurality of virtual packet brokers. The device may determine one or more actions to be implemented based on the one or more metrics. The device may cause the one or more actions to be implemented in the network.

BACKGROUND

Multi-access edge computing (MEC) devices are provided for monitoringcloud RANs (CRANs) and traffic aggregation points (TAPs) in networks. ACRAN may be a cloud-native software solution for handling RANfunctionality. CRANs enable greater flexibility and versatility to bothlarge-scale and centralized 5G network deployments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1F are diagrams of an example associated with automated remotenetwork performance monitoring.

FIG. 2 is a diagram of an example environment in which systems and/ormethods described herein may be implemented.

FIG. 3 is a diagram of example components of one or more devices of FIG.2.

FIG. 4 is a flowchart of an example process relating to automated remotenetwork performance monitoring.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings may identify the same or similar elements.

In some instances, a user device may request access, via a network node,to a service provided via multi-access edge computing (MEC). The networknode may be associated with a wireless network that provides access toMEC. The network node may facilitate a connection between the userdevice and a MEC node based on a geographical location of the userdevice and/or the MEC node. For example, the network node may receivethe request including a domain name and convert the domain name into anetwork address (e.g., an internet protocol (IP) address) of the MECnode that is geographically closest to the user device.

MEC devices are provided for cloud radio access networks (CRANs) andtraffic aggregation points (TAPs) in a network. The TAPs may involveclusters of base stations for aggregating traffic. A TAP may aggregatemultiple CRANs. A probe system may use probes to monitor performanceindicators and customer performance issues at CRANs and TAPs. The probesmay perform key performance indicator (KPI) calculations and storerelated packets. However, the quantity of CRANs and TAPs in a networkmay be large, and the cost of installing probes at all of the CRANs andTAPs may be too expensive. A session aggregation point (SAP) of thenetwork may include a stack of probes, and may not be able to monitortraffic at all of the CRANs or TAPs. Without the functionality of suchprobes monitoring the CRANs and the TAPs, the network may sufferperformance issues that contribute to wasted time, power, processingresources, and signaling resources.

In some implementations, a probe system may deploy virtual packetbrokers (vPBs) on commercial off-the-self (COTS) hardware in CRANs andTAPs to enable network traffic filtering. Traffic may be filtered basedon virtual internet protocol (VIP) addresses, subnets, or tuples. ThevPBs may be lightweight and inexpensive. The vPBs may have no storage,are more passive, and may not calculate key performance indicators(KPIs). The vPBs may be COTS vPBs. The vPBs may be software executing onCOTS hardware or on a COTS packet broker. The vPBs may also be virtualPBs executing on a server. A TAP may be part of a visibility system,where traffic that is observed and copied remotely can be passed asvisibility traffic. The vPBs in the CRANs and TAPs may pass visibilitytraffic that is of interest on demand or according to an automatedschedule to a SAP where probes are aggregated. The vPBs may enablefull-time simple network management protocol (SNMP) polling of some orall visibility traffic, including tenant traffic separation to determinebandwidth utilization in a multi-tenant environment. The vPBs may enableCRAN and TAP MEC troubleshooting and packet capturing on demand. Bydeploying vPBs, network operators may eliminate the need to installprobes at all CRAN and TAP locations. As a result, the probe system mayenable the network to monitor and improve performance, which may causethe network to conserve processing resources and signaling resources.Network providers may also reduce costs.

FIGS. 1A-1F are diagrams of an example 100 associated with automatedremote network performance monitoring. As shown in FIGS. 1A-1F, example100 includes clusters of base stations (e.g., gNBs), TAPs, and CRANs.Each CRAN may include a network device 110, an MEC device 120, and a vPB115. Multiple CRANs may be aggregated at a TAP, and TAPs may beaggregated at an SAP. The vPBs 115 may be deployed on COTS devices. EachTAP may also include an MEC device. Example 100 also shows an SAP with apacket broker 125 and a stack of probes 130. The probe system 135 mayobtain remote traffic from a large quantity of inexpensive vPBs 115. Forexample, an optical tap may split some light on a fiber cable andprovide a copy of traffic to a vPB 115. The probe system 135 may providetraffic information to the stack of probes 130, which can performcalculations. For example, the vPB 115 may forward a copy of all of thetraffic to the probes 130, forward only MEC traffic, or filter trafficfor a subnet or customer of interest. The more expensive probes 130 maycalculate KPIs, but the probes 130 may have limited capacity. However,the less expensive vPBs 115 may be left on full time or switched to anon-demand model, based on the capacity of the probes 130. For example,if the probes 130 have capacity, the vPBs may be on all the time. If theprobes 130 have more limited capacity, the vPBs may operate on demandand/or filter for traffic of interest.

Example 100 further shows a probe system 135, which may include one ormore devices that may control the vPBs.

FIG. 1A shows a probe system 135 that determines one or more parametersfor filtering network traffic. The probe system 135 may operate with anetwork that includes a plurality of vPBs provided for a plurality ofCRANs and a plurality of TAPs. The parameters may filter network trafficbased on VIP addresses, virtual local area network (VLAN), subnets,tuples (e.g., 5-tuples), a subset of traffic of interest, and/or SNMPsof the network traffic. As shown in FIG. 1A, and by reference number140, probe system 135 may provide the one or more parameters to the vPBs115, to cause the vPBs 115 to filter the network traffic to obtainnetwork visibility traffic.

The probe system 135 may receive data identifying the vPBs 115, generatea user interface (UI) based on the data, and provide the user interfacefor display. The vPBs 115 may be accessible via a single graphic UI. Anegressing visibility port may timeout and be disabled after 24 hours toeliminate over-subscription of unified transport (UT) links or probecapacity.

As shown by reference number 145, probe system 135 may receive, from oneor more probes of an SAP of the network, one or more metrics calculatedbased on the network visibility traffic by the vPBs 115. The metrics maybe associated with an availability, latency, utilization, and/or jitterof a CRAN or a TAP.

As shown by reference number 150, the probe system 135 may determine oneor more actions to be implemented based on the metrics. As shown byreference number 155, the probe system 135 may cause the actions to beimplemented in the network. In some implementations, the probe system135 may dispatch a technician to service a network device associatedwith one of the CRANs or one of the TAPs, dispatch an autonomous vehicleto service a network device associated with a CRAN or a TAP, or order areplacement network device to replace a network device associated with aCRAN or TAP. The probe system 135 may also determine and cause otheractions to be implemented in the network.

In some implementations, the probe system 135 may configure probes 130for automated remote performance sampling. The probe system 135 maycycle through (e.g., daily, hourly) performance sampling of CRANs and/orTAPs, based on a capacity of the probes 130. As shown by FIG. 1C, and byreference number 160, the probe system 135 may receive data identifyingbandwidths (e.g., available backhaul bandwidths) of the vPBs 115 and theprobes 130. As shown by reference number 165, the probe system 165 maydetermine a schedule for performance sampling based on the dataidentifying the bandwidths.

Probe capacity may be reserved for on-demand probing, including formulti-tenant environments. Packet broker 125 may cause vPBs 115 toutilize optical taps in CRANs, TAPs, and/or an SAP between backhaul MECentities and MEC tenants to determine bandwidth utilization. The vPBsmay receive copies of traffic (e.g., packets) from the optical tap(which creates copies), determine how to filter the traffic, and thensend the filtered traffic to a probe 130 for KPI calculation. This mayinclude full-time SNMP polling of all visibility traffic. The probesystem 135 may pass visibility traffic of interest on demand by openingup or throttling an egressing port to a unified transport link. That is,the probe system 135 may turn the vPBs on and off on demand, based onneed.

As shown by FIG. 1D, and by reference number 170, the probe system 135may cause the vPBs 115 to implement the schedule for the performancesampling. For example, some probes 130 may be scheduled for CRAN 1 for24 hour periods on Monday, Thursday, and Sunday. Some probes 130 may bescheduled for CRAN 2 for 24 hour periods on Tuesday and Friday. Someprobes 130 may be scheduled for CRAN 3 for 24 hour periods on Wednesdayand Saturday.

As shown by reference number 175, the probe system 135 may receive, fromthe probes 130, network performance data generated based on the vPBs 115implementing the schedule for the performance sampling. Networkperformance data may be received only during scheduled time frames.

In some implementations, the probe system 135 may use the vPBs 115 toobtain network visibility traffic. As shown in FIG. 1E, and by referencenumber 180, the probe system 135 may receive an instruction to resumeobtaining the network visibility traffic. As shown by reference number185, the probe system 135 may provide, to the vPBs 115 and based on theinstruction, the parameters for filtering the network traffic to thenetwork visibility traffic. As shown by FIG. 1F, and by reference number190, the probe system 135 may receive, from the one or more probes, oneor more additional metrics calculated based on the network visibilitytraffic by the vPBs 115. The probe system may determine one or moreadditional actions to be implemented based on the one or more additionalmetrics and cause the one or more additional actions to be implementedin the network.

In some implementations, the prove system 135 may provide parametersthat cause a first set of the vPBs 115 to not capture the networktraffic, and cause a second set of the vPBs 115 to capture the networktraffic, filter the network traffic to the network visibility traffic,and provide the network visibility traffic to the probes 130.

FIG. 2 is a diagram of an example environment 200 in which systemsand/or methods described herein may be implemented. As shown in FIG. 2,environment 200 may include a probe system 201, which may include one ormore elements of and/or may execute within a cloud computing system 202.The cloud computing system 202 may include one or more elements 203-213,as described in more detail below. As further shown in FIG. 2,environment 200 may include a probe system 201, a cloud computing system202, a network 220, one or more gNBs 105, one or more network devices110, one or more vPBs 15, one or more MECs 120, multiple probes 130, anda packet broker 125. Devices and/or elements of environment 200 mayinterconnect via wired connections and/or wireless connections.

The cloud computing system 202 includes computing hardware 203, aresource management component 204, a host operating system (OS) 205,and/or one or more virtual computing systems 206. The resourcemanagement component 204 may perform virtualization (e.g., abstraction)of computing hardware 203 to create the one or more virtual computingsystems 206. Using virtualization, the resource management component 204enables a single computing device (e.g., a computer, a server, and/orthe like) to operate like multiple computing devices, such as bycreating multiple isolated virtual computing systems 206 from computinghardware 203 of the single computing device. In this way, computinghardware 203 can operate more efficiently, with lower power consumption,higher reliability, higher availability, higher utilization, greaterflexibility, and lower cost than using separate computing devices.

Computing hardware 203 includes hardware and corresponding resourcesfrom one or more computing devices. For example, computing hardware 203may include hardware from a single computing device (e.g., a singleserver) or from multiple computing devices (e.g., multiple servers),such as multiple computing devices in one or more data centers. Asshown, computing hardware 203 may include one or more processors 207,one or more memories 208, one or more storage components 209, and/or oneor more networking components 210. Examples of a processor, a memory, astorage component, and a networking component (e.g., a communicationcomponent) are described elsewhere herein.

The resource management component 204 includes a virtualizationapplication (e.g., executing on hardware, such as computing hardware203) capable of virtualizing computing hardware 203 to start, stop,and/or manage one or more virtual computing systems 206. For example,the resource management component 204 may include a hypervisor (e.g., abare-metal or Type 1 hypervisor, a hosted or Type 2 hypervisor, and/orthe like) or a virtual machine monitor, such as when the virtualcomputing systems 206 are virtual machines 211. Additionally, oralternatively, the resource management component 204 may include acontainer manager, such as when the virtual computing systems 206 arecontainers 212. In some implementations, the resource managementcomponent 204 executes within and/or in coordination with a hostoperating system 205.

A virtual computing system 206 includes a virtual environment thatenables cloud-based execution of operations and/or processes describedherein using computing hardware 203. As shown, a virtual computingsystem 206 may include a virtual machine 211, a container 212, a hybridenvironment 213 that includes a virtual machine and a container, and/orthe like. A virtual computing system 206 may execute one or moreapplications using a file system that includes binary files, softwarelibraries, and/or other resources required to execute applications on aguest operating system (e.g., within the virtual computing system 206)or the host operating system 205.

Although the probe system 201 may include one or more elements 203-213of the cloud computing system 202, may execute within the cloudcomputing system 202, and/or may be hosted within the cloud computingsystem 202, in some implementations, the probe system 201 may not becloud-based (e.g., may be implemented outside of a cloud computingsystem) or may be partially cloud-based. For example, the probe system201 may include one or more devices that are not part of the cloudcomputing system 202, such as device 300 of FIG. 3, which may include astandalone server or another type of computing device. The probe system201 may perform one or more operations and/or processes described inmore detail elsewhere herein, such as for probe system 135.

Network 220 includes one or more wired and/or wireless networks. Forexample, network 220 may include a cellular network, a public landmobile network (PLMN), a local area network (LAN), a wide area network(WAN), a private network, the Internet, and/or the like, and/or acombination of these or other types of networks. The network 220 enablescommunication among the devices of environment 200. The network device110 may be a network entity in a CRAN that handles functionality for theCRAN, including for a vPB and/or an MEC 120. The MEC 120 may facilitatemoving computing of traffic and services from cloud computing system 202closer to an edge of the network 220. The packet broker 125 may help toprovide network packet data to the probe system 135 for analysis.

The number and arrangement of devices and networks shown in FIG. 2 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 2. Furthermore, two or more devices shown in FIG. 2 may beimplemented within a single device, or a single device shown in FIG. 2may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 200 may perform one or more functions described as beingperformed by another set of devices of environment 200.

FIG. 3 is a diagram of example components of a device 300, which maycorrespond to probe system 201. In some implementations, probe system201 may include one or more devices 300 and/or one or more components ofdevice 300. As shown in FIG. 3, device 300 may include a bus 310, aprocessor 320, a memory 330, a storage component 340, an input component350, an output component 360, and a communication component 370.

Bus 310 includes a component that enables wired and/or wirelesscommunication among the components of device 300. Processor 320 includesa central processing unit, a graphics processing unit, a microprocessor,a controller, a microcontroller, a digital signal processor, afield-programmable gate array, an application-specific integratedcircuit, and/or another type of processing component. Processor 320 isimplemented in hardware, firmware, or a combination of hardware andsoftware. In some implementations, processor 320 includes one or moreprocessors capable of being programmed to perform a function. Memory 330includes a random access memory, a read only memory, and/or another typeof memory (e.g., a flash memory, a magnetic memory, and/or an opticalmemory).

Storage component 340 stores information and/or software related to theoperation of device 300. For example, storage component 340 may includea hard disk drive, a magnetic disk drive, an optical disk drive, a solidstate disk drive, a compact disc, a digital versatile disc, and/oranother type of non-transitory computer-readable medium. Input component350 enables device 300 to receive input, such as user input and/orsensed inputs. For example, input component 350 may include a touchscreen, a keyboard, a keypad, a mouse, a button, a microphone, a switch,a sensor, a global positioning system component, an accelerometer, agyroscope, and/or an actuator. Output component 360 enables device 300to provide output, such as via a display, a speaker, and/or one or morelight-emitting diodes. Communication component 370 enables device 300 tocommunicate with other devices, such as via a wired connection and/or awireless connection. For example, communication component 370 mayinclude a receiver, a transmitter, a transceiver, a modem, a networkinterface card, and/or an antenna.

Device 300 may perform one or more processes described herein. Forexample, a non-transitory computer-readable medium (e.g., memory 330and/or storage component 340) may store a set of instructions (e.g., oneor more instructions, code, software code, and/or program code) forexecution by processor 320. Processor 320 may execute the set ofinstructions to perform one or more processes described herein. In someimplementations, execution of the set of instructions, by one or moreprocessors 320, causes the one or more processors 320 and/or the device300 to perform one or more processes described herein. In someimplementations, hardwired circuitry may be used instead of or incombination with the instructions to perform one or more processesdescribed herein. Thus, implementations described herein are not limitedto any specific combination of hardware circuitry and software.

The number and arrangement of components shown in FIG. 3 are provided asan example. Device 300 may include additional components, fewercomponents, different components, or differently arranged componentsthan those shown in FIG. 3. Additionally, or alternatively, a set ofcomponents (e.g., one or more components) of device 300 may perform oneor more functions described as being performed by another set ofcomponents of device 300.

FIG. 4 is a flowchart of an example process 400 associated with systemsand methods for automated remote network performance monitoring. In someimplementations, one or more process blocks of FIG. 4 may be performedby a device (e.g., device of probe system 135, device of probe system201). In some implementations, one or more process blocks of FIG. 4 maybe performed by another device or a group of devices separate from orincluding the device, such as MEC 120, network device 110, packet broker125, and/or gNB 105. Additionally, or alternatively, one or more processblocks of FIG. 4 may be performed by one or more components of device300, such as processor 320, memory 330, storage component 340, inputcomponent 350, output component 360, and/or communication component 370.

A network may include a plurality of virtual packet brokers. The virtualpacket brokers may be provided for a plurality of cloud random accessnetworks and a plurality of traffic aggregation points. As shown in FIG.4, process 400 may include determining one or more parameters forfiltering network traffic of the network (block 410). For example, thedevice may determine one or more parameters for filtering networktraffic, of a network that includes a plurality of virtual packetbrokers provided for a plurality of cloud random access networks and aplurality of traffic aggregation points, as described above. In someimplementations, each of the plurality of virtual packet brokers isdeployed on a commercial off-the-shelf device.

As further shown in FIG. 4, process 400 may include providing the one ormore parameters to the plurality of virtual packet brokers, to cause theplurality of virtual packet brokers to filter the network traffic toobtain network visibility traffic (block 420). For example, the devicemay provide the one or more parameters to the plurality of virtualpacket brokers, to cause the plurality of virtual packet brokers tofilter the network traffic to obtain network visibility traffic, asdescribed above.

As further shown in FIG. 4, process 400 may include receiving, from oneor more probes of a session aggregation point of the network, one ormore metrics calculated based on the network visibility traffic by theplurality of virtual packet brokers (block 430). For example, the devicemay receive, from one or more probes of a session aggregation point ofthe network, one or more metrics calculated based on the networkvisibility traffic by the plurality of virtual packet brokers, asdescribed above. In some implementations, the one or more metricsinclude one or more of a metric associated with an availability of oneof the plurality of cloud random access networks or one of the pluralityof traffic aggregation points, a metric associated with a latency of oneof the plurality of cloud random access networks or one of the pluralityof traffic aggregation points, a metric associated with utilization ofone of the plurality of cloud random access networks or one of theplurality of traffic aggregation points, or a metric associated withjitter of one of the plurality of cloud random access networks or one ofthe plurality of traffic aggregation points.

In some implementations, process 400 includes receiving data identifyingbandwidths of the plurality of virtual packet brokers and the one ormore probes, determining a schedule for performance sampling based onthe data identifying the bandwidths, causing the plurality of virtualpacket brokers to implement the schedule for the performance sampling,and receiving, from the one or more probes, network performance datagenerated based on the plurality of virtual packet brokers implementingthe schedule for the performance sampling.

As further shown in FIG. 4, process 400 may include determining one ormore actions to be implemented based on the one or more metrics (block440). For example, the device may determine one or more actions to beimplemented based on the one or more metrics, as described above.

In some implementations, process 400 includes receiving an instructionto resume obtaining the network visibility traffic, providing, to theplurality of virtual packet brokers and based on the instruction, theone or more parameters for filtering the network traffic to the networkvisibility traffic, receiving, from the one or more probes, one or moreadditional metrics calculated based on the network visibility traffic bythe plurality of virtual packet brokers, determining one or moreadditional actions to be implemented based on the one or more additionalmetrics, and causing the one or more additional actions to beimplemented in the network.

As further shown in FIG. 4, process 400 may include causing the one ormore actions to be implemented in the network (block 450). For example,the device may cause the one or more actions to be implemented in thenetwork, as described above. In some implementations, process 400includes determining one or more additional actions to be implementedbased on the network performance data, and causing the one or moreadditional actions to be implemented in the network.

In some implementations, causing the one or more actions to beimplemented comprises one or more of dispatching a technician to servicea network device associated with one of the plurality of cloud randomaccess networks or one of the plurality of traffic aggregation points,dispatching an autonomous vehicle to service a network device associatedwith one of the plurality of cloud random access networks or one of theplurality of traffic aggregation points, or ordering a replacementnetwork device to replace a network device associated with one of theplurality of cloud random access networks or one of the plurality oftraffic aggregation points.

Although FIG. 4 shows example blocks of process 400, in someimplementations, process 400 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 4. Additionally, or alternatively, two or more of theblocks of process 400 may be performed in parallel.

By using probe system 135, a centralized cloud platform may receive vPBbandwidth and probe bandwidth, and determine when to turn the vPBs onand off to focus on specific traffic. Deploying the vPBs and probes asdescribed above renders great cost savings and conserves processing andsignaling resources.

As used herein, the term “component” is intended to be broadly construedas hardware, firmware, or a combination of hardware and software. Itwill be apparent that systems and/or methods described herein may beimplemented in different forms of hardware, firmware, and/or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods are described herein without reference tospecific software code—it being understood that software and hardwarecan be used to implement the systems and/or methods based on thedescription herein.

As used herein, satisfying a threshold may, depending on the context,refer to a value being greater than the threshold, greater than or equalto the threshold, less than the threshold, less than or equal to thethreshold, equal to the threshold, not equal to the threshold, or thelike.

To the extent the aforementioned implementations collect, store, oremploy personal information of individuals, it should be understood thatsuch information shall be used in accordance with all applicable lawsconcerning protection of personal information. Additionally, thecollection, storage, and use of such information can be subject toconsent of the individual to such activity, for example, through wellknown “opt-in” or “opt-out” processes as can be appropriate for thesituation and type of information. Storage and use of personalinformation can be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of various implementations. In fact,many of these features may be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below may directly depend on only one claim, thedisclosure of various implementations includes each dependent claim incombination with every other claim in the claim set. As used herein, aphrase referring to “at least one of” a list of items refers to anycombination of those items, including single members. As an example, “atleast one of: a, b, or c” is intended to cover a, b, c, a-b, a-c, b-c,and a-b-c, as well as any combination with multiple of the same item.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Further, asused herein, the article “the” is intended to include one or more itemsreferenced in connection with the article “the” and may be usedinterchangeably with “the one or more.” Furthermore, as used herein, theterm “set” is intended to include one or more items (e.g., relateditems, unrelated items, or a combination of related and unrelateditems), and may be used interchangeably with “one or more.” Where onlyone item is intended, the phrase “only one” or similar language is used.Also, as used herein, the terms “has,” “have,” “having,” or the like areintended to be open-ended terms. Further, the phrase “based on” isintended to mean “based, at least in part, on” unless explicitly statedotherwise. Also, as used herein, the term “or” is intended to beinclusive when used in a series and may be used interchangeably with“and/or,” unless explicitly stated otherwise (e.g., if used incombination with “either” or “only one of”).

In the preceding specification, various example embodiments have beendescribed with reference to the accompanying drawings. It will, however,be evident that various modifications and changes may be made thereto,and additional embodiments may be implemented, without departing fromthe broader scope of the invention as set forth in the claims thatfollow. The specification and drawings are accordingly to be regarded inan illustrative rather than restrictive sense.

1. A method, comprising: determining, by a device, one or moreparameters for filtering network traffic of a network that includes aplurality of virtual packet brokers provided for a plurality of cloudrandom access networks and a plurality of traffic aggregation points,wherein a cloud random access network, of the plurality of cloud randomaccess networks, is a cloud-native solution for handling random accessnetwork functionality; providing, by the device, the one or moreparameters to the plurality of virtual packet brokers, to cause theplurality of virtual packet brokers to filter the network traffic toobtain network visibility traffic; receiving, by the device and from oneor more probes of a session aggregation point of the network, one ormore metrics based on the network visibility traffic by the plurality ofvirtual packet brokers, wherein the one or more metrics includeavailability, latency, or utilization of one of the plurality of cloudrandom access networks or one of the plurality of traffic aggregationpoints; determining, by the device, one or more actions to beimplemented based on the one or more metrics, wherein the one or moreimplemented actions are associated with the one of the plurality ofcloud random access networks or the one of the plurality of trafficaggregation points; and causing, by the device, the one or more actionsto be implemented in the network.
 2. The method of claim 1, furthercomprising: receiving data identifying bandwidths of the plurality ofvirtual packet brokers and the one or more probes; determining aschedule for performance sampling based on the data identifying thebandwidths, causing the plurality of virtual packet brokers to implementthe schedule for the performance sampling; and receiving, from the oneor more probes, network performance data generated based on theplurality of virtual packet brokers implementing the schedule for theperformance sampling.
 3. The method of claim 2, further comprising:determining one or more additional actions to be implemented based onthe network performance data; and causing the one or more additionalactions to be implemented in the network.
 4. The method of claim 2,further comprising: receiving an instruction to resume obtaining thenetwork visibility traffic; providing, to the plurality of virtualpacket brokers and based on the instruction, the one or more parametersfor filtering the network traffic to the network visibility traffic;receiving, from the one or more probes, one or more additional metricscalculated based on the network visibility traffic by the plurality ofvirtual packet brokers; determining one or more additional actions to beimplemented based on the one or more additional metrics; and causing theone or more additional actions to be implemented in the network.
 5. Themethod of claim 4, wherein causing the one or more additional actions tobe implemented comprises one or more of: dispatching a technician toservice a network device associated with one of the plurality of cloudrandom access networks or one of the plurality of traffic aggregationpoints; dispatching an autonomous vehicle to service a network deviceassociated with one of the plurality of cloud random access networks orone of the plurality of traffic aggregation points; or ordering areplacement network device to replace a network device associated withone of the plurality of cloud random access networks or one of theplurality of traffic aggregation points.
 6. The method of claim 4,wherein the one or more additional metrics also include a metricassociated with jitter of one of the plurality of traffic aggregationpoints.
 7. The method of claim 1, wherein each of the plurality ofvirtual packet brokers is deployed on a commercial off-the-shelf device.8. A device, comprising: one or more processors configured to: determineone or more parameters for filtering network traffic, of a network thatincludes a plurality of virtual packet brokers provided for a pluralityof cloud random access networks and a plurality of traffic aggregationpoints, wherein a cloud random access network, of the plurality of cloudrandom access networks, is a cloud-native solution for handling randomaccess network functionality; provide the one or more parameters to theplurality of virtual packet brokers, to cause the plurality of virtualpacket brokers to filter the network traffic to obtain networkvisibility traffic; receive, from one or more probes of a sessionaggregation point of the network, two or more metrics based on thenetwork visibility traffic by the plurality of virtual packet brokers,wherein the two or more metrics include two or more of: a metricassociated with an availability of one of the plurality of cloud randomaccess networks or one of the plurality of traffic aggregation points, ametric associated with a latency of one of the plurality of cloud randomaccess networks or one of the plurality of traffic aggregation points,or a metric associated with utilization of one of the plurality of cloudrandom access networks or one of the plurality of traffic aggregationpoints; determine one or more actions to be implemented based on the twoor more metrics, wherein the one or more implemented actions areassociated with the one of the plurality of cloud random access networksor the one of the plurality of traffic aggregation points; and cause theone or more actions to be implemented in the network.
 9. The device ofclaim 8, wherein each of the plurality of cloud random access networksand each of the plurality of traffic aggregation points includes amobile edge computing device.
 10. The device of claim 8, wherein the oneor more parameters include one or more of: a parameter for filtering thenetwork traffic based on virtual Internet protocol addresses of thenetwork traffic, a parameter for filtering the network traffic based onsubnets of the network traffic, a parameter for filtering the networktraffic based on tuples of the network traffic, or a parameter forfiltering the network traffic based on a simple network managementprotocol.
 11. The device of claim 8, wherein the one or more processorsare further configured to: receive data identifying the plurality ofvirtual packet brokers and the one or more probes; generate a userinterface based on the data identifying the plurality of virtual packetbrokers and the one or more probes; and provide the user interface fordisplay.
 12. The device of claim 8, wherein the one or more parameterscause the plurality of virtual packet brokers to: filter the networktraffic to the network visibility traffic, and provide the networkvisibility traffic to the one or more probes.
 13. The device of claim 8,wherein the one or more parameters cause a first set of the plurality ofvirtual packet brokers to not capture the network traffic, and cause asecond set of the plurality of virtual packet brokers to capture thenetwork traffic, filter the network traffic to the network visibilitytraffic, and provide the network visibility traffic to the one or moreprobes.
 14. The device of claim 8, wherein each of the plurality ofcloud random access networks is associated with a corresponding clusterof gNodeBs of the network.
 15. A non-transitory computer-readable mediumstoring a set of instructions, the set of instructions comprising: oneor more instructions that, when executed by one or more processors of adevice, cause the device to: determine one or more parameters forfiltering network traffic, of a network that includes a plurality ofvirtual packet brokers provided for a plurality of cloud random accessnetworks and a plurality of traffic aggregation points, wherein a cloudrandom access network, of the plurality of cloud random access networks,is a cloud-native solution for handling random access networkfunctionality; provide the one or more parameters to the plurality ofvirtual packet brokers, to cause the plurality of virtual packet brokersto filter the network traffic to obtain network visibility traffic;receive, from one or more probes of a session aggregation point of thenetwork, one or more metrics calculated based on the network visibilitytraffic by the plurality of virtual packet brokers, wherein the one ormore metrics include availability, latency, or utilization of one of theplurality of cloud random access networks or one of the plurality oftraffic aggregation points; receive data identifying the plurality ofvirtual packet brokers and the one or more probes; generate a userinterface based on the one or more metrics and the data identifying theplurality of virtual packet brokers and the one or more probes; andprovide the user interface for display.
 16. The non-transitorycomputer-readable medium of claim 15, wherein the one or moreinstructions further cause the device to: receive data identifyingbandwidths of the plurality of virtual packet brokers and the one ormore probes; determine a schedule for performance sampling based on thedata identifying the bandwidths; cause the plurality of virtual packetbrokers to implement the schedule for the performance sampling; receive,from the one or more probes, network performance data generated based onthe plurality of virtual packet brokers implementing the schedule forthe performance sampling; determine one or more actions to beimplemented based on the network performance data; and cause the one ormore actions to be implemented in the network.
 17. The non-transitorycomputer-readable medium of claim 15, wherein the one or moreinstructions further cause the device to one or more of: dispatch atechnician to service a network device associated with one of theplurality of cloud random access networks or one of the plurality oftraffic aggregation points; dispatch an autonomous vehicle to service anetwork device associated with one of the plurality of cloud randomaccess networks or one of the plurality of traffic aggregation points;or order a replacement network device to replace a network deviceassociated with one of the plurality of cloud random access networks orone of the plurality of traffic aggregation points.
 18. Thenon-transitory computer-readable medium of claim 15, wherein each of theplurality of cloud random access networks and each of the plurality oftraffic aggregation points includes a mobile edge computing device. 19.The non-transitory computer-readable medium of claim 15, wherein the oneor more parameters include one or more of: a parameter for filtering thenetwork traffic based on virtual Internet protocol addresses of thenetwork traffic, a parameter for filtering the network traffic based onsubnets of the network traffic, a parameter for filtering the networktraffic based on tuples of the network traffic, or a parameter forfiltering the network traffic based on a simple network managementprotocol.
 20. The non-transitory computer-readable medium of claim 15,wherein the one or more parameters cause a first set of the plurality ofvirtual packet brokers to not capture the network traffic, and cause asecond set of the plurality of virtual packet brokers to capture thenetwork traffic, filter the network traffic to the network visibilitytraffic, and provide the network visibility traffic to the one or moreprobes.